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    Predicting Project Performance in the Construction Industry

    Source: Journal of Construction Engineering and Management:;2020:;Volume ( 146 ):;issue: 005
    Author:
    Rayan Assaad
    ,
    Islam H. El-Adaway
    ,
    Ibrahim S. Abotaleb
    DOI: 10.1061/(ASCE)CO.1943-7862.0001797
    Publisher: ASCE
    Abstract: Regardless of the different project characteristics in the construction industry, cost and schedule overruns are always regarded as being of paramount importance in the project controls area. Numerous research efforts have been directed to forecast the aforementioned two important project variables using different modeling techniques. However, no prior work is believed to have offered an integrated approach to estimating the performance of construction projects. This critical knowledge gap is compounded even more by the evolving complexities and uncertainties in today’s construction industry. This paper creates a holistic framework to evaluate project progress and to predict its performance by incorporating a broad spectrum of inputs. The objectives are to (1) quantify the impacts of the risks related to the performance of projects in terms of cost and schedule; (2) formulate a holistic assessment model; and (3) correlate the developed system to predict cost and time at project completion. To this end, a multistep research methodology was utilized. First, for data collection, a survey was distributed and filled by 63 construction experts to study the effects of 25 performance risks that have shown to be the most important based on a meta-analysis of the literature in a previous study. Second, mathematical and statistical analysis techniques were used to develop a model that maps the investigated project risks to both cost and schedule performance. Steps included fitting parametric and nonparametric distributions, calculating cost overruns, verifying the model, and providing guidelines for using the proposed model. Third, for application, a hypothetical dataset was used to demonstrate the use of the model, its ability to deduce real-world behavior patterns, and associated limitations. The developed framework contributes to the body of knowledge by providing a novel model that improves project performance in terms of prediction, control, management, analysis, and decision making based on an individualized assessment of different risk indicators. This study is valuable for the construction industry because it allows all stakeholders to evaluate the performance of construction projects based on a list of variables, ultimately ensuring more effective and efficient delivery and execution of projects.
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      Predicting Project Performance in the Construction Industry

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    contributor authorRayan Assaad
    contributor authorIslam H. El-Adaway
    contributor authorIbrahim S. Abotaleb
    date accessioned2022-01-30T19:22:15Z
    date available2022-01-30T19:22:15Z
    date issued2020
    identifier other%28ASCE%29CO.1943-7862.0001797.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4265170
    description abstractRegardless of the different project characteristics in the construction industry, cost and schedule overruns are always regarded as being of paramount importance in the project controls area. Numerous research efforts have been directed to forecast the aforementioned two important project variables using different modeling techniques. However, no prior work is believed to have offered an integrated approach to estimating the performance of construction projects. This critical knowledge gap is compounded even more by the evolving complexities and uncertainties in today’s construction industry. This paper creates a holistic framework to evaluate project progress and to predict its performance by incorporating a broad spectrum of inputs. The objectives are to (1) quantify the impacts of the risks related to the performance of projects in terms of cost and schedule; (2) formulate a holistic assessment model; and (3) correlate the developed system to predict cost and time at project completion. To this end, a multistep research methodology was utilized. First, for data collection, a survey was distributed and filled by 63 construction experts to study the effects of 25 performance risks that have shown to be the most important based on a meta-analysis of the literature in a previous study. Second, mathematical and statistical analysis techniques were used to develop a model that maps the investigated project risks to both cost and schedule performance. Steps included fitting parametric and nonparametric distributions, calculating cost overruns, verifying the model, and providing guidelines for using the proposed model. Third, for application, a hypothetical dataset was used to demonstrate the use of the model, its ability to deduce real-world behavior patterns, and associated limitations. The developed framework contributes to the body of knowledge by providing a novel model that improves project performance in terms of prediction, control, management, analysis, and decision making based on an individualized assessment of different risk indicators. This study is valuable for the construction industry because it allows all stakeholders to evaluate the performance of construction projects based on a list of variables, ultimately ensuring more effective and efficient delivery and execution of projects.
    publisherASCE
    titlePredicting Project Performance in the Construction Industry
    typeJournal Paper
    journal volume146
    journal issue5
    journal titleJournal of Construction Engineering and Management
    identifier doi10.1061/(ASCE)CO.1943-7862.0001797
    page04020030
    treeJournal of Construction Engineering and Management:;2020:;Volume ( 146 ):;issue: 005
    contenttypeFulltext
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